Distributed Path Compression for Piecewise Linear Morse-Smale Segmentations and Connected Components

TL;DR

This paper presents a scalable distributed algorithm for Morse-Smale segmentation and connected components computation, integrated with TTK, demonstrating high performance on large-scale datasets with up to 4096^3 vertices.

Contribution

We adapt a path compression algorithm for distributed environments and extend it to efficiently compute connected components on large, complex datasets.

Findings

Successful scaling to datasets with 4096^3 vertices

Efficient computation on distributed structured and unstructured grids

Seamless integration with the Topology ToolKit (TTK)

Abstract

This paper describes the adaptation of a well-scaling parallel algorithm for computing Morse-Smale segmentations based on path compression to a distributed computational setting. Additionally, we extend the algorithm to efficiently compute connected components in distributed structured and unstructured grids, based either on the connectivity of the underlying mesh or a feature mask. Our implementation is seamlessly integrated with the distributed extension of the Topology ToolKit (TTK), ensuring robust performance and scalability. To demonstrate the practicality and efficiency of our algorithms, we conducted a series of scaling experiments on large-scale datasets, with sizes of up to 4096^3 vertices on up to 64 nodes and 768 cores.